Lumpy Skin Disease Outbreaks in Africa, Europe, and Asia (2005–2022): Multiple Change Point Analysis and Time Series Forecast

Abstract

LSD is an important transboundary disease affecting the cattle industry worldwide. The objectives of this study were to determine trends and significant change points, and to forecast the number of LSD outbreak reports in Africa, Europe, and Asia. LSD outbreak report data (January 2005 to January 2022) from the World Organization for Animal Health were analyzed. We determined statistically significant change points in the data using binary segmentation, and forecast the number of LSD reports using auto-regressive moving average (ARIMA) and neural network auto-regressive (NNAR) models. Four significant change points were identified for each continent. The year between the third and fourth change points (2016–2019) in the African data was the period with the highest mean of number of LSD reports. All change points of LSD outbreaks in Europe corresponded with massive outbreaks during 2015–2017. Asia had the highest number of LSD reports in 2019 after the third detected change point in 2018. For the next three years (2022–2024), both ARIMA and NNAR forecast a rise in the number of LSD reports in Africa and a steady number in Europe. However, ARIMA predicts a stable number of outbreaks in Asia, whereas NNAR predicts an increase in 2023–2024. This study provides information that contributes to a better understanding of the epidemiology of LSD.

Poxvirus Infections in Dairy Farms and Transhumance Cattle Herds in Nigeria

“…The major finding of our study included the fact that the Nigerian LSDV isolates were similar to other known African isolates from Sudan, Ethiopia, South Africa, and Egypt, and European isolates from Bulgaria, Greece, Serbia, Turkey, and isolates from Russia, Kazakhstan, Iraq, and Israel, but different from recombinant LSDV field isolates from China, Thailand, Taiwan, and Russia [ 66 ]. On the other end, the Nigerian PCPV isolates were clustered with the Zambian and Botswana isolates.…”

Cross-correlation and time series analysis of rabies in different animal species in Nepal from 2005 to 2018

“…To identify significant changes in rabies occurrences during the period from 2005 to 2018, change point analysis was applied to the obtained dataset [ 38 , 46 , 47 ]. These occurrences were assumed to follow the Poisson distribution due to the count nature of the data.…”

“…Time series analysis relies on previous data to uncover the underlying time-dependent structure and project future trends [ 37 ]. On the other hand, change point analysis detects sudden structural changes in time series analysis, providing factual context for the trend [ 38 ]. Recently, numerous epidemiological studies have used a variety of time-series techniques to create prediction models that can be used with a wide range of data [ [39] , [40] , [41] ].…”

Lumpy skin disease as an emerging infectious disease

“…In particular, the two organizations focused on the LSD outbreak in the Balkan and Caucasus countries [ 12 ]. On the other hand, epidemiological aspects and control strategies related to LSD in Asian countries remain to be analyzed, even though some studies have been done and reported [ 1 2 3 4 8 13 ].…”